Papers
5
Total Citations
54
H-Index
4
About
Jiao Jiao Li is a pioneering researcher at the intersection of biomedical engineering, artificial intelligence, and sensor technology. Her work primarily focuses on advancing surgical techniques through robotic and computer-assisted systems, developing intelligent signal processing for brain-computer interfaces (BCIs), and improving inertial sensor calibration. Li’s most impactful contribution is a comprehensive Bayesian network meta-analysis comparing robot-assisted surgery, computer navigation, and conventional methods in total knee arthroplasty, which has garnered 18 citations and provides critical evidence for surgical decision-making. She also leads innovation in neurorehabilitation with the EEG_GLT-Net, a novel deep learning framework that optimizes EEG graph structures for real-time motor imagery classification, achieving 13 citations and offering transformative potential for stroke patients. Additionally, Li developed an efficient, low-cost calibration method for triaxial gyroscopes that reduces procedure time to just one minute (11 citations), and her Google Trends analysis revealed surging public interest in robotic versus computer-navigated joint arthroplasty (8 citations). Her work on cascaded geometric feature modulation networks for point cloud processing further demonstrates her versatility in AI-driven engineering. With a growing citation record and applications spanning orthopedics, rehabilitation, and sensor technology, Li is shaping the future of precision medicine and human-machine interaction.
Research Focus
Key Achievements
Top Papers
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- 3An Efficient Calibration Method for Triaxial Gyroscope11 citations · 2021
- 4
- 5Cascaded geometric feature modulation network for point cloud processing4 citations · 2022